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Description/Abstract

This contribution presents a novel methodology for automated optimal design of a MEMS accelerometer with Sigma-Delta force-feedback control loop from user defined high-level performance specifications and design constraints. The proposed approach is based on a simulation-based optimization technology using a genetic algorithm. The layout of the mechanical sensing element is generated simultaneously with the optimal design parameters of the Sigma-Delta control loop. As currently available implementations of AMS HDL languages are not suitable for complex mixed-technology system optimisation, the algorithm as well as aa fast dedicated sigma-delta accelerometer simulator have been implemented in C++. The underlying accelerometer model includes the sense finger dynamics described by a partial differential equation, which enables accurate performance prediction of the sensing element embedded in a in mixed-technology control loop.